TOP2B Enzymatic Activity on Promoters and Introns Modulates Multiple Oncogenes in Human Gliomas.

PURPOSE: The epigenetic mechanisms involved in transcriptional regulation leading to malignant phenotype in gliomas remains poorly understood. Topoisomerase IIB (TOP2B), an enzyme that decoils and releases torsional forces in DNA, is overexpressed in a subset of gliomas. Therefore, we investigated its role in epigenetic regulation in these tumors. EXPERIMENTAL DESIGN: To investigate the role of TOP2B in epigenetic regulation in gliomas, we performed paired chromatin immunoprecipitation sequencing for TOP2B and RNA-sequencing analysis of glioma cell lines with and without TOP2B inhibition and in human glioma specimens. These experiments were complemented with assay for transposase-accessible chromatin using sequencing, gene silencing, and mouse xenograft experiments to investigate the function of TOP2B and its role in glioma phenotypes. RESULTS: We discovered that TOP2B modulates transcription of multiple oncogenes in human gliomas. TOP2B regulated transcription only at sites where it was enzymatically active, but not at all native binding sites. In particular, TOP2B activity localized in enhancers, promoters, and introns of PDGFRA and MYC, facilitating their expression. TOP2B levels and genomic localization was associated with PDGFRA and MYC expression across glioma specimens, which was not seen in nontumoral human brain tissue. In vivo, TOP2B knockdown of human glioma intracranial implants prolonged survival and downregulated PDGFRA. CONCLUSIONS: Our results indicate that TOP2B activity exerts a pleiotropic role in transcriptional regulation of oncogenes in a subset of gliomas promoting a proliferative phenotype.

N-quinoline-benzenesulfonamide derivatives exert potent anti-lymphoma effect by targeting NF-κB.

We previously identified the N-quinoline-benzenesulfonamide (NQBS) scaffold as a potent inhibitor of nuclear factor-κB (NF-κB) translocation. Now, we report the structure-activity relationship of compounds with the NQBS scaffold in models of diffuse large B-cell lymphoma (DLBCL). We identified CU-O42, CU-O47, and CU-O75 as NQBS analogs with the most potent cytotoxic activity in DLBCL lines. Their anti-lymphoma effect was mediated by NF-κB sequestration to the cytoplasm of DLBCL cells. Internal Coordinates Mechanics analysis suggested direct binding between CU-O75 and IκBα/p50/p65 which leads to the stabilization of the NF-κB trimer. A whole cellular thermal shift assay confirmed direct binding of the NQBS to IκBα, an inhibitory component of the IκBα/p50/p65 trimer. Lymphoma cell line sequencing revealed CU-O75 induced downregulation of NF-κB-dependent genes and DeMAND analysis identified IκBα as one of the top protein targets for CU-O75. CU-O42 was potent in inhibiting tumor growth in two mouse models of aggressive lymphomas.

Ribosomal protein S11 influences glioma response to TOP2 poisons.

Topoisomerase II poisons are one of the most common class of chemotherapeutics used in cancer. We and others had shown that a subset of glioblastomas, the most malignant of all primary brain tumors in adults, is responsive to TOP2 poisons. To identify genes that confer susceptibility to this drug in gliomas, we performed a genome-scale CRISPR knockout screen with etoposide. Genes involved in protein synthesis and DNA damage were implicated in etoposide susceptibility. To define potential biomarkers for TOP2 poisons, CRISPR hits were overlapped with genes whose expression correlates with susceptibility to this drug across glioma cell lines, revealing ribosomal protein subunit RPS11, 16, and 18 as putative biomarkers for response to TOP2 poisons. Loss of RPS11 led to resistance to etoposide and doxorubicin and impaired the induction of proapoptotic gene APAF1 following treatment. The expression of these ribosomal subunits was also associated with susceptibility to TOP2 poisons across cell lines from gliomas and multiple other cancers.

Experimental microdissection enables functional harmonisation of pancreatic cancer subtypes.

OBJECTIVE: Pancreatic ductal adenocarcinoma (PDA) has among the highest stromal fractions of any cancer and this has complicated attempts at expression-based molecular classification. The goal of this work is to profile purified samples of human PDA epithelium and stroma and examine their respective contributions to gene expression in bulk PDA samples. DESIGN: We used laser capture microdissection (LCM) and RNA sequencing to profile the expression of 60 matched pairs of human PDA malignant epithelium and stroma samples. We then used these data to train a computational model that allowed us to infer tissue composition and generate virtual compartment-specific expression profiles from bulk gene expression cohorts. RESULTS: Our analysis found significant variation in the tissue composition of pancreatic tumours from different public cohorts. Computational removal of stromal gene expression resulted in the reclassification of some tumours, reconciling functional differences between different cohorts. Furthermore, we established a novel classification signature from a total of 110 purified human PDA stroma samples, finding two groups that differ in the extracellular matrix-associated and immune-associated processes. Lastly, a systematic evaluation of cross-compartment subtypes spanning four patient cohorts indicated partial dependence between epithelial and stromal molecular subtypes. CONCLUSION: Our findings add clarity to the nature and number of molecular subtypes in PDA, expand our understanding of global transcriptional programmes in the stroma and harmonise the results of molecular subtyping efforts across independent cohorts.

Elucidating synergistic dependencies in lung adenocarcinoma by proteome-wide signaling-network analysis.

To understand drug combination effect, it is necessary to decipher the interactions between drug targets-many of which are signaling molecules. Previously, such signaling pathway models are largely based on the compilation of literature data from heterogeneous cellular contexts. Indeed, de novo reconstruction of signaling interactions from large-scale molecular profiling is still lagging, compared to similar efforts in transcriptional and protein-protein interaction networks. To address this challenge, we introduce a novel algorithm for the systematic inference of protein kinase pathways, and applied it to published mass spectrometry-based phosphotyrosine profile data from 250 lung adenocarcinoma (LUAD) samples. The resulting network includes 43 TKs and 415 inferred, LUAD-specific substrates, which were validated at >60% accuracy by SILAC assays, including "novel' substrates of the EGFR and c-MET TKs, which play a critical oncogenic role in lung cancer. This systematic, data-driven model supported drug response prediction on an individual sample basis, including accurate prediction and validation of synergistic EGFR and c-MET inhibitor activity in cells lacking mutations in either gene, thus contributing to current precision oncology efforts.

FGF-induced Pea3 transcription factors program the genetic landscape for cell fate determination.

FGF signaling is a potent inducer of lacrimal gland development in the eye, capable of transforming the corneal epithelium into glandular tissues. Here, we show that genetic ablation of the Pea3 family of transcription factors not only disrupted the ductal elongation and branching of the lacrimal gland, but also biased the lacrimal gland epithelium toward an epidermal cell fate. Analysis of high-throughput gene expression and chromatin immunoprecipitation data revealed that the Pea3 genes directly control both the positive and negative feedback loops of FGF signaling. Importantly, Pea3 genes are also required to suppress aberrant Notch signaling which, if gone unchecked, can compromise lacrimal gland development by preventing the expression of both Sox and Six family genes. These results demonstrate that Pea3 genes are key FGF early response transcriptional factors, programing the genetic landscape for cell fate determination.

The number of titrated microRNA species dictates ceRNA regulation.

microRNAs (miRNAs) play key roles in cancer, but their propensity to couple their targets as competing endogenous RNAs (ceRNAs) has only recently emerged. Multiple models have studied ceRNA regulation, but these models did not account for the effects of co-regulation by miRNAs with many targets. We modeled ceRNA and simulated its effects using established parameters for miRNA/mRNA interaction kinetics while accounting for co-regulation by multiple miRNAs with many targets. Our simulations suggested that co-regulation by many miRNA species is more likely to produce physiologically relevant context-independent couplings. To test this, we studied the overlap of inferred ceRNA networks from four tumor contexts-our proposed pan-cancer ceRNA interactome (PCI). PCI was composed of interactions between genes that were co-regulated by nearly three-times as many miRNAs as other inferred ceRNA interactions. Evidence from expression-profiling datasets suggested that PCI interactions are predictive of gene expression in 12 independent tumor- and non-tumor contexts. Biochemical assays confirmed ceRNA couplings for two PCI subnetworks, including oncogenes CCND1, HIF1A and HMGA2, and tumor suppressors PTEN, RB1 and TP53. Our results suggest that PCI is enriched for context-independent interactions that are coupled by many miRNA species and are more likely to be context independent.

High-throughput validation of ceRNA regulatory networks.

BACKGROUND: MicroRNAs (miRNAs) play multiple roles in tumor biology. Interestingly, reports from multiple groups suggest that miRNA targets may be coupled through competitive stoichiometric sequestration. Specifically, computational models predicted and experimental assays confirmed that miRNA activity is dependent on miRNA target abundance, and consequently, changes in the abundance of some miRNA targets lead to changes to the regulation and abundance of their other targets. The resulting indirect regulatory influence between miRNA targets resembles competition and has been dubbed competitive endogenous RNA (ceRNA). Recent studies have questioned the physiological relevance of ceRNA interactions, our ability to accurately predict these interactions, and the number of genes that are impacted by ceRNA interactions in specific cellular contexts. RESULTS: To address these concerns, we reverse engineered ceRNA networks (ceRNETs) in breast and prostate adenocarcinomas using context-specific TCGA profiles, and tested whether ceRNA interactions can predict the effects of RNAi-mediated gene silencing perturbations in PC3 and MCF7 cells._ENREF_22 Our results, based on tests of thousands of inferred ceRNA interactions that are predicted to alter hundreds of cancer genes in each of the two tumor contexts, confirmed statistically significant effects for half of the predicted targets. CONCLUSIONS: Our results suggest that the expression of a significant fraction of cancer genes may be regulated by ceRNA interactions in each of the two tumor contexts.

Bone morphogenetic protein and Notch signalling crosstalk in poor-prognosis, mesenchymal-subtype colorectal cancer.

The functional role of bone morphogenetic protein (BMP) signalling in colorectal cancer (CRC) is poorly defined, with contradictory results in cancer cell line models reflecting the inherent difficulties of assessing a signalling pathway that is context-dependent and subject to genetic constraints. By assessing the transcriptional response of a diploid human colonic epithelial cell line to BMP ligand stimulation, we generated a prognostic BMP signalling signature, which was applied to multiple CRC datasets to investigate BMP heterogeneity across CRC molecular subtypes. We linked BMP and Notch signalling pathway activity and function in human colonic epithelial cells, and normal and neoplastic tissue. BMP induced Notch through a γ-secretase-independent interaction, regulated by the SMAD proteins. In homeostasis, BMP/Notch co-localization was restricted to cells at the top of the intestinal crypt, with more widespread interaction in some human CRC samples. BMP signalling was downregulated in the majority of CRCs, but was conserved specifically in mesenchymal-subtype tumours, where it interacts with Notch to induce an epithelial-mesenchymal transition (EMT) phenotype. In intestinal homeostasis, BMP-Notch pathway crosstalk is restricted to differentiating cells through stringent pathway segregation. Conserved BMP activity and loss of signalling stringency in mesenchymal-subtype tumours promotes a synergistic BMP-Notch interaction, and this correlates with poor patient prognosis. BMP signalling heterogeneity across CRC subtypes and cell lines can account for previous experimental contradictions. Crosstalk between the BMP and Notch pathways will render mesenchymal-subtype CRC insensitive to γ-secretase inhibition unless BMP activation is concomitantly addressed. © 2017 The Authors. Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Quantitative Tyrosine Phosphoproteomics of Epidermal Growth Factor Receptor (EGFR) Tyrosine Kinase Inhibitor-treated Lung Adenocarcinoma Cells Reveals Potential Novel Biomarkers of Therapeutic Response.

Mutations in the Epidermal growth factor receptor (EGFR) kinase domain, such as the L858R missense mutation and deletions spanning the conserved sequence 747LREA750, are sensitive to tyrosine kinase inhibitors (TKIs). The gatekeeper site residue mutation, T790M accounts for around 60% of acquired resistance to EGFR TKIs. The first generation EGFR TKIs, erlotinib and gefitinib, and the second generation inhibitor, afatinib are FDA approved for initial treatment of EGFR mutated lung adenocarcinoma. The predominant biomarker of EGFR TKI responsiveness is the presence of EGFR TKI-sensitizing mutations. However, 30-40% of patients with EGFR mutations exhibit primary resistance to these TKIs, underscoring the unmet need of identifying additional biomarkers of treatment response. Here, we sought to characterize the dynamics of tyrosine phosphorylation upon EGFR TKI treatment of mutant EGFR-driven human lung adenocarcinoma cell lines with varying sensitivity to EGFR TKIs, erlotinib and afatinib. We employed stable isotope labeling with amino acids in cell culture (SILAC)-based quantitative mass spectrometry to identify and quantify tyrosine phosphorylated peptides. The proportion of tyrosine phosphorylated sites that had reduced phosphorylation upon erlotinib or afatinib treatment correlated with the degree of TKI-sensitivity. Afatinib, an irreversible EGFR TKI, more effectively inhibited tyrosine phosphorylation of a majority of the substrates. The phosphosites with phosphorylation SILAC ratios that correlated with the TKI-sensitivity of the cell lines include sites on kinases, such as EGFR-Y1197 and MAPK7-Y221, and adaptor proteins, such as SHC1-Y349/350, ERRFI1-Y394, GAB1-Y689, STAT5A-Y694, DLG3-Y705, and DAPP1-Y139, suggesting these are potential biomarkers of TKI sensitivity. DAPP1, is a novel target of mutant EGFR signaling and Y-139 is the major site of DAPP1 tyrosine phosphorylation. We also uncovered several off-target effects of these TKIs, such as MST1R-Y1238/Y1239 and MET-Y1252/1253. This study provides unique insight into the TKI-mediated modulation of mutant EGFR signaling, which can be applied to the development of biomarkers of EGFR TKI response.

Synergistic antileukemic therapies in NOTCH1-induced T-ALL.

The Notch1 gene is a major oncogenic driver and therapeutic target in T-cell acute lymphoblastic leukemia (T-ALL). However, inhibition of NOTCH signaling with γ-secretase inhibitors (GSIs) has shown limited antileukemic activity in clinical trials. Here we performed an expression-based virtual screening to identify highly active antileukemic drugs that synergize with NOTCH1 inhibition in T-ALL. Among these, withaferin A demonstrated the strongest cytotoxic and GSI-synergistic antileukemic effects in vitro and in vivo. Mechanistically, network perturbation analyses showed eIF2A-phosphorylation-mediated inhibition of protein translation as a critical mediator of the antileukemic effects of withaferin A and its interaction with NOTCH1 inhibition. Overall, these results support a role for anti-NOTCH1 therapies and protein translation inhibitor combinations in the treatment of T-ALL.

Novel Hybrid Phenotype Revealed in Small Cell Lung Cancer by a Transcription Factor Network Model That Can Explain Tumor Heterogeneity.

Small cell lung cancer (SCLC) is a devastating disease due to its propensity for early invasion and refractory relapse after initial treatment response. Although these aggressive traits have been associated with phenotypic heterogeneity, our understanding of this association remains incomplete. To fill this knowledge gap, we inferred a set of 33 transcription factors (TF) associated with gene signatures of the known neuroendocrine/epithelial (NE) and non-neuroendocrine/mesenchymal-like (ML) SCLC phenotypes. The topology of this SCLC TF network was derived from prior knowledge and was simulated using Boolean modeling. These simulations predicted that the network settles into attractors, or TF expression patterns, that correlate with NE or ML phenotypes, suggesting that TF network dynamics underlie the emergence of heterogeneous SCLC phenotypes. However, several cell lines and patient tumor specimens failed to correlate with either the NE or ML attractors. By flow cytometry, single cells within these cell lines simultaneously expressed surface markers of both NE and ML differentiation, confirming the existence of a "hybrid" phenotype. Upon exposure to standard-of-care cytotoxic drugs or epigenetic modifiers, NE and ML cell populations converged toward the hybrid state, suggesting possible escape from treatment. Our findings indicate that SCLC phenotypic heterogeneity can be specified dynamically by attractor states of a master regulatory TF network. Thus, SCLC heterogeneity may be best understood as states within an epigenetic landscape. Understanding phenotypic transitions within this landscape may provide insights to clinical applications. Cancer Res; 77(5); 1063-74. ©2016 AACR.

An ID2-dependent mechanism for VHL inactivation in cancer.

Mechanisms that maintain cancer stem cells are crucial to tumour progression. The ID2 protein supports cancer hallmarks including the cancer stem cell state. HIFα transcription factors, most notably HIF2α (also known as EPAS1), are expressed in and required for maintenance of cancer stem cells (CSCs). However, the pathways that are engaged by ID2 or drive HIF2α accumulation in CSCs have remained unclear. Here we report that DYRK1A and DYRK1B kinases phosphorylate ID2 on threonine 27 (Thr27). Hypoxia downregulates this phosphorylation via inactivation of DYRK1A and DYRK1B. The activity of these kinases is stimulated in normoxia by the oxygen-sensing prolyl hydroxylase PHD1 (also known as EGLN2). ID2 binds to the VHL ubiquitin ligase complex, displaces VHL-associated Cullin 2, and impairs HIF2α ubiquitylation and degradation. Phosphorylation of Thr27 of ID2 by DYRK1 blocks ID2-VHL interaction and preserves HIF2α ubiquitylation. In glioblastoma, ID2 positively modulates HIF2α activity. Conversely, elevated expression of DYRK1 phosphorylates Thr27 of ID2, leading to HIF2α destabilization, loss of glioma stemness, inhibition of tumour growth, and a more favourable outcome for patients with glioblastoma.

Elucidation and Pharmacological Targeting of Novel Molecular Drivers of Follicular Lymphoma Progression.

Follicular lymphoma, the most common indolent subtype of non-Hodgkin lymphoma, is associated with a relatively long overall survival rate ranging from 6 to 10 years from the time of diagnosis. However, in 20% to 60% of follicular lymphoma patients, transformation to aggressive diffuse large B-cell lymphoma (DLBCL) reduces median survival to only 1.2 years. The specific functional and genetic determinants of follicular lymphoma transformation remain elusive, and genomic alterations underlying disease advancement have only been identified for a subset of cases. Therefore, to identify candidate drivers of follicular lymphoma transformation, we performed systematic analysis of a B-cell-specific regulatory model exhibiting follicular lymphoma transformation signatures using the Master Regulator Inference algorithm (MARINa). This analysis revealed FOXM1, TFDP1, ATF5, HMGA1, and NFYB to be candidate master regulators (MR) contributing to disease progression. Accordingly, validation was achieved through synthetic lethality assays in which RNAi-mediated silencing of MRs individually or in combination reduced the viability of (14;18)-positive DLBCL (t-DLBCL) cells. Furthermore, specific combinations of small-molecule compounds targeting synergistic MR pairs induced loss of viability in t-DLBCL cells. Collectively, our findings indicate that MR analysis is a valuable method for identifying bona fide contributors to follicular lymphoma transformation and may therefore guide the selection of compounds to be used in combinatorial treatment strategies.

Disruption of KMT2D perturbs germinal center B cell development and promotes lymphomagenesis.

Mutations in the gene encoding the KMT2D (or MLL2) methyltransferase are highly recurrent and occur early during tumorigenesis in diffuse large B cell lymphoma (DLBCL) and follicular lymphoma (FL). However, the functional consequences of these mutations and their role in lymphomagenesis are unknown. Here we show that FL- and DLBCL-associated KMT2D mutations impair KMT2D enzymatic activity, leading to diminished global H3K4 methylation in germinal-center (GC) B cells and DLBCL cells. Conditional deletion of Kmt2d early during B cell development, but not after initiation of the GC reaction, results in an increase in GC B cells and enhances B cell proliferation in mice. Moreover, genetic ablation of Kmt2d in mice overexpressing Bcl2 increases the incidence of GC-derived lymphomas resembling human tumors. These findings suggest that KMT2D acts as a tumor suppressor gene whose early loss facilitates lymphomagenesis by remodeling the epigenetic landscape of the cancer precursor cells. Eradication of KMT2D-deficient cells may thus represent a rational therapeutic approach for targeting early tumorigenic events.

Elucidating Compound Mechanism of Action by Network Perturbation Analysis.

Genome-wide identification of the mechanism of action (MoA) of small-molecule compounds characterizing their targets, effectors, and activity modulators represents a highly relevant yet elusive goal, with critical implications for assessment of compound efficacy and toxicity. Current approaches are labor intensive and mostly limited to elucidating high-affinity binding target proteins. We introduce a regulatory network-based approach that elucidates genome-wide MoA proteins based on the assessment of the global dysregulation of their molecular interactions following compound perturbation. Analysis of cellular perturbation profiles identified established MoA proteins for 70% of the tested compounds and elucidated novel proteins that were experimentally validated. Finally, unknown-MoA compound analysis revealed altretamine, an anticancer drug, as an inhibitor of glutathione peroxidase 4 lipid repair activity, which was experimentally confirmed, thus revealing unexpected similarity to the activity of sulfasalazine. This suggests that regulatory network analysis can provide valuable mechanistic insight into the elucidation of small-molecule MoA and compound similarity.

Interrogation of a context-specific transcription factor network identifies novel regulators of pluripotency.

The predominant view of pluripotency regulation proposes a stable ground state with coordinated expression of key transcription factors (TFs) that prohibit differentiation. Another perspective suggests a more complexly regulated state involving competition between multiple lineage-specifying TFs that define pluripotency. These contrasting views were developed from extensive analyses of TFs in pluripotent cells in vitro. An experimentally validated, genome-wide repertoire of the regulatory interactions that control pluripotency within the in vivo cellular contexts is yet to be developed. To address this limitation, we assembled a TF interactome of adult human male germ cell tumors (GCTs) using the Algorithm for the Accurate Reconstruction of Cellular Pathways (ARACNe) to analyze gene expression profiles of 141 tumors comprising pluripotent and differentiated subsets. The network (GCT(Net)) comprised 1,305 TFs, and its ingenuity pathway analysis identified pluripotency and embryonal development as the top functional pathways. We experimentally validated GCT(Net) by functional (silencing) and biochemical (ChIP-seq) analysis of the core pluripotency regulatory TFs POU5F1, NANOG, and SOX2 in relation to their targets predicted by ARACNe. To define the extent of the in vivo pluripotency network in this system, we ranked all TFs in the GCT(Net) according to sharing of ARACNe-predicted targets with those of POU5F1 and NANOG using an odds-ratio analysis method. To validate this network, we silenced the top 10 TFs in the network in H9 embryonic stem cells. Silencing of each led to downregulation of pluripotency and induction of lineage; 7 of the 10 TFs were identified as pluripotency regulators for the first time.

Aberrant epithelial GREM1 expression initiates colonic tumorigenesis from cells outside the stem cell niche.

Hereditary mixed polyposis syndrome (HMPS) is characterized by the development of mixed-morphology colorectal tumors and is caused by a 40-kb genetic duplication that results in aberrant epithelial expression of the gene encoding mesenchymal bone morphogenetic protein antagonist, GREM1. Here we use HMPS tissue and a mouse model of the disease to show that epithelial GREM1 disrupts homeostatic intestinal morphogen gradients, altering cell fate that is normally determined by position along the vertical epithelial axis. This promotes the persistence and/or reacquisition of stem cell properties in Lgr5-negative progenitor cells that have exited the stem cell niche. These cells form ectopic crypts, proliferate, accumulate somatic mutations and can initiate intestinal neoplasia, indicating that the crypt base stem cell is not the sole cell of origin of colorectal cancer. Furthermore, we show that epithelial expression of GREM1 also occurs in traditional serrated adenomas, sporadic premalignant lesions with a hitherto unknown pathogenesis, and these lesions can be considered the sporadic equivalents of HMPS polyps.

A community effort to assess and improve drug sensitivity prediction algorithms.

Predicting the best treatment strategy from genomic information is a core goal of precision medicine. Here we focus on predicting drug response based on a cohort of genomic, epigenomic and proteomic profiling data sets measured in human breast cancer cell lines. Through a collaborative effort between the National Cancer Institute (NCI) and the Dialogue on Reverse Engineering Assessment and Methods (DREAM) project, we analyzed a total of 44 drug sensitivity prediction algorithms. The top-performing approaches modeled nonlinear relationships and incorporated biological pathway information. We found that gene expression microarrays consistently provided the best predictive power of the individual profiling data sets; however, performance was increased by including multiple, independent data sets. We discuss the innovations underlying the top-performing methodology, Bayesian multitask MKL, and we provide detailed descriptions of all methods. This study establishes benchmarks for drug sensitivity prediction and identifies approaches that can be leveraged for the development of new methods.